One could very well say the same thing about the weather: a hundred years ago, no one in their right mind (which is a tricky way of denoting all but the ones with the most foresight) would have guessed that we would ever be able to accurately predict the weather ten days into the future. But incredible advances in physics now allows us to do just that. Even though the weather systems are very sensitive to many factors, the combination of the Navier-Stokes equations and a continuous effort to measure weather all over the world, we are now comfortable trusting that the weather forecasts are more accurate than guessing.

In this article by Carl Zimmer from 2014 several researchers explain how the same type of forecasting could potentially be applied to evolutionary biology. Particularly, it is not at all inconceivable that we will be able to predict flu virus evolution, thereby better making vaccines and saving lives. Microbial evolution, it turns out, often has much more repeatable outcomes than what is traditionally thought. Recent research strongly suggest that this is the case, for example when bacteria evolve the same solutions again and again to the same problems.

Here’s a simulation with an example of that:

In this very simple example, you’ll have to admit it’s pretty easy to predict where the population is going to go, yes? (See the full video on youtube for more about fitness landscapes.)

One way to think of evolutionary forecasting is by obtaining as much data as possible about the fitness of genetic variants. If we know which variants (bacteria and viruses are the best candidate organisms) are most successful in making copies of themselves, then we can potentially make predictions of how they will evolve in the near future – just like with the weather.

The problem is that measuring fitness for many many genetic variants is still difficult. It means sequencing many individual organisms, and it means measuring fitness for each one of those variants. The resulting fitness landscape (i.e., fitness as a function of the genotype) is the last of three parameters needed to predict the simplest evolutionary systems. The other two are the population size and the mutation rate. Both of these are fortunately much easier to measure than the fitness landscape. So the fitness landscape remains the biggest obstacle. But it has only taken a few years to get quite far with measurements, and I don’t think it is at all inconceivable that we could have evolutionary forecasts for certain viruses and bacteria within the next few decades.

Returning to Gould, I predict that his lasting impact on evolutionary biology will be similar to Lamarck‘s: His “rewinding the tape of life” will be the quintessential error that people will keep referring to when talking about evolutionary forecasting.

To be more specific: I predict that 187 years from Gould’s death (i.e., by 2189), when his name is mentioned, most people will immediately think of the tape first. And additionally that the idea has been somewhat refuted, since they then will be pretty good at evolutionary forecasting. (Lamarck died 187 years ago.)

My friend Larry Moran, who blogs at Sandwalk, is a staunch Gould admirer, and he asked me these questions in regard o my prediction:

Do you really believe that if we reran the tape of life we would always end up with a continent like Australia where marsupials outnumber placental mammals?

Do you believe that every possible scenario would result in hundreds of species of dinosaurs that go extinct about 65 million years ago?

Is the great Permian extinction always going to happen?

Will an oxygen evolving complex always arise in primitive cyanobacterium about 2.5 billion years ago?

Are you convinced that replaying the tape of life will always produce eukaryotes with introns and complex spliceosomes?

Will no replay ever produce highly intelligent New World Monkeys?

Are poisonous mushrooms absolutely necessary?

Will the platypus always evolve and never go extinct?

If we ever find another planet that’s very similar to Earth do you expect to find intelligent mammals and maple trees?

And Larry made his own prediction:

Gould will be remembered for his attack on adaptationism and reminding us that there’s more to evolution than natural selection. He will be remembered for teaching us about contingency and exaptation. He will be remembered for hierarchical theory. Above all, he will be remembered for making us all aware of the fact that evolution is a lot more complicated than we think.

One objection to the tape metaphor is that it is not well-defined. Does “rewinding the tape of life” mean that everything starts out the same? The initial conditions are *exactly* the same? What about the random events that influence evolution, will they be exactly the same or are they different? Are we talking about the environmental effects (weather, plate tectonics, ET events) being the same or not? Would mutations be identical or just drawn from the same distribution? Some people may have a clear idea of these things and thus feel confident of what the metaphor really means, but I know for a fact that there is not a general consensus about this, with several evolutionary biologists that I have talked to having differing views about its interpretation. We can all agree that randomness is very important in evolution, but not what kind of randomness is part of the metaphor.

In answer to Larry’s questions above, one answer is no, not that specifically. Stochasticity (randomness) is too strong a factor, and future evolutionary events are contingent on earlier events.

On the other hand, it may be that stochasticity doesn’t mean that evolution is unpredictable, just like it is not unpredictable what will happen when you heat a pot of water, even though we can’t predict the path of every individual water molecule.

On the first hand again, if we’re talking about, say, evolution on other planets, then no, we cannot expect those exact outcomes. However, Gould also denied that humans would be a repeat outcome if the tape was rewinded, but it is not clearly defined what we mean by “humans” in this context. If by humans we mean intelligent bipedal tetrapods with a head on top, then I do think there are very good reasons to believe that such creatures could evolve again and again, and be a feature on many planet that harbor life throughout the universe.

Back on the second hand, one can argue that every event that ever happens is determined by previous physical states. Things are only as random as we are unable to foresee the next event. A random mutation is only random because we don’t know the factors that determine it, or because we don’t have the data to predict it. In other words, if we rewind until some time point, everything else is the same up until that time point, so there are good reasons to believe that all future random events would be identical to the first run, and we would thus get exactly what we got the first time.

Bjørn Østman is an evolutionary biologist postdoc working in the BEACON Center for the Study of Evolution in Action.

I am interested in many aspects of evolution. I work in computational biology, using various approaches to learn about fundamental processes of evolution. Bioinformatics is good for learning about real genes (data generously supplied by other researchers), and simulations are good for testing the mechanisms of evolution. I am particularly interested in how populations and organisms adapt to changing environments, both at the genetic and phenotypic level. Lately my research has focused on the evolutionary dynamics of populations evolving in rugged fitness landscapes.